Object models are used for many different applications such as gaming, computer graphics, augmented reality (AR), virtual reality (VR), prototyping, robotics, architecture, and design. For example, in AR and VR applications, the familiarity of daily object models is exploited to provide a user a more realistic experience. Models of objects can be acquired directly by the original computer-aided design (CAD), manual modeling, or using three-dimensional (3D) scanning techniques. However, the original CAD models are not often provided by the manufacturer and may also not account for real-word deformations, defects, or other manufacturing differences. Manual modeling can be time-intensive and may require experts in the field to measure and model free-form objects. Present day 3D scanning solutions may provide increased accuracy and cost efficiencies in generating 3D model of objects.
Typical 3D scanning techniques utilize a camera to scan the object. One difficulty that can occur with such 3D scanning techniques is the inability to map occluded surfaces of the object. Any occluded surface has an unknown geometry and could include cavities, protuberances, or complex topology patches. Those unknown surfaces can result in an inaccurate modelling of the object. Accordingly, numerous algorithms have been developed in an attempt to remedy such deficiencies of the 3D scanning process. For example, various signal and image processing filters have been leveraged to smooth out noise and fill depth holes.